Wonderchat

Automatically extracts text and structured content from PDF files and converts them into a machine-readable knowledge base for chatbot responses. The system parses document structure, tables, and text to enable the chatbot to answer questions based on PDF content.

Crawls and indexes content from a provided website URL, extracting text, FAQs, and structured data to populate the chatbot's knowledge base. Enables chatbots trained on live website content without manual document uploads.

Records and stores conversation logs between users and the chatbot, enabling review of interactions, quality assessment, and identification of knowledge gaps. Provides visibility into chatbot performance and user satisfaction.

Manages situations where the chatbot cannot find relevant information in the knowledge base by providing fallback responses or escalation options. Prevents the chatbot from generating incorrect answers when knowledge is insufficient.

Generates a fully functional AI chatbot from ingested knowledge in minutes without requiring code, configuration, or machine learning expertise. The chatbot is immediately ready to answer questions based on the provided knowledge source.

Generates an embeddable JavaScript widget that can be placed on any website to display the chatbot as a floating chat interface. Handles styling, positioning, and communication between the website and chatbot backend.

Connects the chatbot to a Slack workspace, allowing the bot to answer questions and provide support directly within Slack channels and direct messages. Enables internal team use and customer support through Slack.

Connects the chatbot to Microsoft Teams, enabling the bot to answer questions and provide support within Teams channels and direct messages. Supports both internal team use and customer-facing support scenarios.

Combines knowledge from multiple PDFs and/or website URLs into a single unified knowledge base that the chatbot uses to answer questions. Allows users to build comprehensive chatbots from diverse content sources.

Processes user questions and generates natural language responses based on the indexed knowledge base. Uses NLP to match questions to relevant knowledge base content and formulates contextual answers.

Provides a free tier with limited message quotas and basic features, allowing users to test the chatbot before committing to paid plans. Tracks usage and enforces rate limits based on subscription level.

Allows users to customize the chatbot's appearance with their brand colors, logo, and name. Provides basic visual customization for the chat widget and responses to match brand identity.